Modeling of the color decay and calculation of the original state: the case of San Telmo (18th century), Seville, Spain
Bibliographic record
Abstract
The mural painting Glorification of the Virgin at Palace of San Telmo (18th century, Seville, Spain) has been analyzed through 161 optical spectra acquired using fiber optic VIS-NIR reflectance spectroscopy, encompassing all the colors present in the painting. In addition, 13 samples were taken from representative areas and analyzed by optical and electronic imaging. These analyses have identified the painting materials and techniques and provide information about the color generation processes through the interaction between different pictorial layers. The color alterations suffered by the painting have been quantified through a mathematical model which yields the original color and attributes. The results find a general darkening and color shift more noticeable for cold colors, showing that the mathematical model is a reliable approach to color correction and supports the use of fiber optic VIS-NIR reflectance as a non-invasive technique for the characterization of cultural heritage. • Alteration of colors at the mural painting Glorification of the Virgen del Buen Aire chapel at San Telmo Palace is measured and modeled. • Reflectance VIS-NIS spectra (161) samples all the colors at the mural painting. A mathematical model that quantifies color alteration is proposed. • The results find a general darkening and color shift, showing that the mathematical model is a reliable approach to color correction and supports the use of fiber optic VIS-NIR reflectance as a non-invasive technique for the characterization of cultural heritage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".